A method is provided that includes generating a visual environment for interactive development of a machine learning (ML) model. The method includes accessing observations of data each of which includes values of independent variables and a dependent variable, and performing an interactive exploratory data analysis (EDA) of the values of a set of the independent variables. The method includes performing an interactive feature construction and selection based on the interactive EDA, and in which select independent variables are selected as or transformed into a set of features for use in building a ML model to predict the dependent variable. The method includes building the ML model using a ML algorithm, the set of features, and a training set produced from the set of features and observations of the data. And the method includes outputting the ML model for deployment to predict the dependent variable for additional observations of the data.
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2. The apparatus of claim 1, wherein the system is an aircraft, and the plurality of observations of the data is flight data for plurality of flights of the aircraft, for each flight of which the values of the plurality of independent variables are measurements of a plurality of properties recorded by an airborne flight recorder from a plurality of sensors or avionic systems during the flight, and the value of the dependent variable is an indication of a condition of the aircraft during the flight.
5. The apparatus of claim 1, wherein the apparatus being caused to perform the interactive feature construction and selection includes being caused to apply the one or more of the select independent variables to a transformation to produce a feature of the set of features, the one or more of the select independent variables or the transformation being selected based on user input via the GUI.
9. The method of claim 8, wherein the system is an aircraft, and the plurality of observations of the data is flight data for plurality of flights of the aircraft, for each flight of which the values of the plurality of independent variables are measurements of a plurality of properties recorded by an airborne flight recorder from a plurality of sensors or avionic systems during the flight, and the value of the dependent variable is an indication of a condition of the aircraft during the flight.
12. The method of claim 8, wherein performing the interactive feature construction and selection includes applying the one or more of the select independent variables to a transformation to produce a feature of the set of features, the one or more of the select independent variables or the transformation being selected based on user input via the GUI.
16. The non-transitory computer-readable storage medium of claim 15, wherein the system is an aircraft, and the plurality of observations of the data is flight data for plurality of flights of the aircraft, for each flight of which the values of the plurality of independent variables are measurements of a plurality of properties recorded by an airborne flight recorder from a plurality of sensors or avionic systems during the flight, and the value of the dependent variable is an indication of a condition of the aircraft during the flight.
19. The non-transitory computer-readable storage medium of claim 15, wherein the feature construction and selection is an interactive feature construction and selection, and the apparatus being caused to perform the feature construction and selection includes being caused to apply the one or more of the select independent variables to a transformation to produce a feature of the set of features, the one or more of the select independent variables or the transformation being selected based on user input via the GUI.
22. The apparatus of claim 3, wherein the apparatus is further caused to build a version of the machine learning model using the machine learning algorithm, the modified set of features, and a modified training set produced from the modified set of features and the plurality of observations of the data.
23. The method of claim 10 further comprising building a version of the machine learning model using the machine learning algorithm, the modified set of features, and a modified training set produced from the modified set of features and the plurality of observations of the data.
24. The apparatus of claim 17, wherein the apparatus is further caused to build a version of the machine learning model using the machine learning algorithm, the modified set of features, and a modified training set produced from the modified set of features and the plurality of observations of the data.
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October 25, 2018
November 15, 2022
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